{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "06da1e50-ad7f-41cd-b53b-6335b62f6c3a",
   "metadata": {},
   "source": [
    "# Realistic Multiuser MIMO OFDM Simulations\n",
    "In this notebook, you will learn how to setup realistic simulations\n",
    "of multiuser MIMO uplink transmissions. Multiple user terminals (UTs)\n",
    "are randomly distributed in a cell sector and communicate with a multi-antenna\n",
    "base station.\n",
    "\n",
    "\n",
    "![layout]()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91114f45-9448-4a5d-b47c-8a6e8e4936dc",
   "metadata": {},
   "source": [
    "The block-diagramm of the system model looks as follows:\n",
    "\n",
    "\n",
    "![System Model]()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f6f1d65-8a8c-45ca-9e35-eb0e54983200",
   "metadata": {},
   "source": [
    "It includes the following components:\n",
    "\n",
    "- 5G LDPC FEC\n",
    "- QAM modulation\n",
    "- OFDM resource grid with configurable pilot pattern\n",
    "- Multiple single-antenna transmitters and a multi-antenna receiver\n",
    "- 3GPP 38.901 UMi, UMa, and RMa channel models and antenna patterns\n",
    "- LS Channel estimation with nearest-neighbor interpolation as well as perfect CSI\n",
    "- LMMSE MIMO equalization\n",
    "\n",
    "You will learn how to setup the topologies required to simulate such scenarios and investigate\n",
    "\n",
    "- the performance over different models, and\n",
    "- the impact of imperfect CSI.\n",
    "\n",
    "We will first walk through the configuration of all components of the system model, before simulating\n",
    "some simple uplink transmissions in the frequency domain. We will then simulate CDFs of the channel condition number\n",
    "and look into frequency-selectivity of the different channel models to understand the reasons for the observed performance differences.\n",
    "\n",
    "It is recommended that you familiarize yourself with the [API documentation](https://nvlabs.github.io/sionna/phy/api/channel.wireless.html) of the `Channel` module\n",
    "and, in particular, the 3GPP 38,901 models that require a substantial amount of configuration.  The last set of simulations in this notebook take some time, especially when you have no GPU available. For this reason, we provide the simulation\n",
    "results directly in the cells generating the figures. Simply uncomment the corresponding lines to show this results."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3001429c-d46a-47e4-8e5f-fa3afc402d73",
   "metadata": {},
   "source": [
    "## Table of Contents\n",
    "* [GPU Configuration and Imports](#GPU-Configuration-and-Imports)\n",
    "* [System Setup](#System-Setup)\n",
    "* [Uplink Transmissions in the Frequency Domain](#Uplink-Transmissions-in-the-Frequency-Domain)\n",
    "    * [Compare Estimated and Actual Frequency Responses](#Compare-Estimated-and-Actual-Frequency-Responses)\n",
    "    * [Understand the Difference Between the Channel Models](#Understand-the-Difference-Between-the-Channel-Models)\n",
    "    * [Setup a Sionna Block for BER simulations](#Setup-a-Sionna-Block-for-BER-simulations)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa4f4cfb-4a31-4a69-aaed-93d21fbb5d21",
   "metadata": {
    "tags": []
   },
   "source": [
    "## GPU Configuration and Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ffb6a229",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:20.981255Z",
     "iopub.status.busy": "2025-03-11T00:48:20.980725Z",
     "iopub.status.idle": "2025-03-11T00:48:23.474556Z",
     "shell.execute_reply": "2025-03-11T00:48:23.473682Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "if os.getenv(\"CUDA_VISIBLE_DEVICES\") is None:\n",
    "    gpu_num = 0 # Use \"\" to use the CPU\n",
    "    os.environ[\"CUDA_VISIBLE_DEVICES\"] = f\"{gpu_num}\"\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'\n",
    "\n",
    "# Import Sionna\n",
    "try:\n",
    "    import sionna.phy\n",
    "except ImportError as e:\n",
    "    import sys\n",
    "    if 'google.colab' in sys.modules:\n",
    "       # Install Sionna in Google Colab\n",
    "       print(\"Installing Sionna and restarting the runtime. Please run the cell again.\")\n",
    "       os.system(\"pip install sionna\")\n",
    "       os.kill(os.getpid(), 5)\n",
    "    else:\n",
    "       raise e\n",
    "\n",
    "# Configure the notebook to use only a single GPU and allocate only as much memory as needed\n",
    "# For more details, see https://www.tensorflow.org/guide/gpu\n",
    "import tensorflow as tf\n",
    "gpus = tf.config.list_physical_devices('GPU')\n",
    "if gpus:\n",
    "    try:\n",
    "        tf.config.experimental.set_memory_growth(gpus[0], True)\n",
    "    except RuntimeError as e:\n",
    "        print(e)\n",
    "# Avoid warnings from TensorFlow\n",
    "tf.get_logger().setLevel('ERROR')\n",
    "\n",
    "# Set random seed for reproducibility\n",
    "sionna.phy.config.seed = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9d3ff139",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:23.478355Z",
     "iopub.status.busy": "2025-03-11T00:48:23.478058Z",
     "iopub.status.idle": "2025-03-11T00:48:23.490820Z",
     "shell.execute_reply": "2025-03-11T00:48:23.490086Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "from sionna.phy import Block\n",
    "from sionna.phy.mimo import StreamManagement\n",
    "from sionna.phy.ofdm import ResourceGrid, ResourceGridMapper, \\\n",
    "                            LSChannelEstimator, LMMSEEqualizer, \\\n",
    "                            RemoveNulledSubcarriers\n",
    "from sionna.phy.channel.tr38901 import Antenna, AntennaArray, UMi, UMa, RMa\n",
    "from sionna.phy.channel import gen_single_sector_topology as gen_topology\n",
    "from sionna.phy.channel import subcarrier_frequencies, cir_to_ofdm_channel, \\\n",
    "                               ApplyOFDMChannel, OFDMChannel\n",
    "from sionna.phy.fec.ldpc import LDPC5GEncoder, LDPC5GDecoder\n",
    "from sionna.phy.mapping import Mapper, Demapper, BinarySource, QAMSource\n",
    "from sionna.phy.utils import ebnodb2no, sim_ber, compute_ber"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15e1b3bb-5c41-4269-9bc8-1b4d7e48124c",
   "metadata": {
    "tags": []
   },
   "source": [
    "## System Setup\n",
    "\n",
    "We will now configure all components of the system model step-by-step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5182bedb-6726-4089-9e0e-9077056f3086",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:23.493629Z",
     "iopub.status.busy": "2025-03-11T00:48:23.493336Z",
     "iopub.status.idle": "2025-03-11T00:48:23.496700Z",
     "shell.execute_reply": "2025-03-11T00:48:23.496086Z"
    }
   },
   "outputs": [],
   "source": [
    "scenario = \"umi\"\n",
    "carrier_frequency = 3.5e9\n",
    "direction = \"uplink\"\n",
    "num_ut = 4 \n",
    "batch_size = 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a20a279c-374a-48f6-8d31-3972a46d1dfa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:23.499606Z",
     "iopub.status.busy": "2025-03-11T00:48:23.499324Z",
     "iopub.status.idle": "2025-03-11T00:48:27.508314Z",
     "shell.execute_reply": "2025-03-11T00:48:27.507644Z"
    }
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the UT antenna array\n",
    "ut_array = Antenna(polarization=\"single\",\n",
    "                   polarization_type=\"V\",\n",
    "                   antenna_pattern=\"omni\",\n",
    "                   carrier_frequency=carrier_frequency)\n",
    "\n",
    "# Define the BS antenna array\n",
    "bs_array = AntennaArray(num_rows=1,\n",
    "                        num_cols=4,\n",
    "                        polarization=\"dual\",\n",
    "                        polarization_type=\"VH\",\n",
    "                        antenna_pattern=\"38.901\",\n",
    "                        carrier_frequency=carrier_frequency)\n",
    "\n",
    "# Create channel model\n",
    "channel_model = UMi(carrier_frequency=carrier_frequency,\n",
    "                    o2i_model=\"low\",\n",
    "                    ut_array=ut_array,\n",
    "                    bs_array=bs_array,\n",
    "                    direction=direction,\n",
    "                    enable_pathloss=False,\n",
    "                    enable_shadow_fading=False)\n",
    "\n",
    "# Generate the topology\n",
    "topology = gen_topology(batch_size, num_ut, scenario)\n",
    "\n",
    "# Set the topology\n",
    "channel_model.set_topology(*topology)\n",
    "\n",
    "# Visualize the topology\n",
    "channel_model.show_topology()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "88fdc090-fe1f-43c6-86b3-1698ec1d0bad",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:27.510783Z",
     "iopub.status.busy": "2025-03-11T00:48:27.510535Z",
     "iopub.status.idle": "2025-03-11T00:48:27.514819Z",
     "shell.execute_reply": "2025-03-11T00:48:27.514177Z"
    }
   },
   "outputs": [],
   "source": [
    "# The number of transmitted streams is equal to the number of UT antennas\n",
    "num_streams_per_tx = 1\n",
    "\n",
    "# Create an RX-TX association matrix\n",
    "# rx_tx_association[i,j]=1 means that receiver i gets at least one stream\n",
    "# from transmitter j. Depending on the transmission direction (uplink or downlink),\n",
    "# the role of UT and BS can change. However, as we have only a single\n",
    "# transmitter and receiver, this does not matter:\n",
    "rx_tx_association = np.zeros([1, num_ut])\n",
    "rx_tx_association[0, :] = 1\n",
    "\n",
    "# Instantiate a StreamManagement object\n",
    "# This determines which data streams are determined for which receiver.\n",
    "# In this simple setup, this is fairly simple. However, it can get complicated\n",
    "# for simulations with many transmitters and receivers.\n",
    "sm = StreamManagement(rx_tx_association, num_streams_per_tx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d90fcba6-b37c-4d46-850a-1662eae3832e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:27.517160Z",
     "iopub.status.busy": "2025-03-11T00:48:27.516917Z",
     "iopub.status.idle": "2025-03-11T00:48:28.101804Z",
     "shell.execute_reply": "2025-03-11T00:48:28.101135Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rg = ResourceGrid(num_ofdm_symbols=14,\n",
    "                  fft_size=128,\n",
    "                  subcarrier_spacing=30e3,\n",
    "                  num_tx=num_ut,\n",
    "                  num_streams_per_tx=num_streams_per_tx,\n",
    "                  cyclic_prefix_length=20,\n",
    "                  pilot_pattern=\"kronecker\",\n",
    "                  pilot_ofdm_symbol_indices=[2,11])\n",
    "rg.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cdc0fa83-8e2b-495f-a5b8-5e8cb4267964",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:28.104302Z",
     "iopub.status.busy": "2025-03-11T00:48:28.103998Z",
     "iopub.status.idle": "2025-03-11T00:48:28.386336Z",
     "shell.execute_reply": "2025-03-11T00:48:28.385486Z"
    }
   },
   "outputs": [],
   "source": [
    "num_bits_per_symbol = 2 # QPSK modulation\n",
    "coderate = 0.5 # The code rate\n",
    "n = int(rg.num_data_symbols*num_bits_per_symbol) # Number of coded bits\n",
    "k = int(n*coderate) # Number of information bits\n",
    "\n",
    "# The binary source will create batches of information bits\n",
    "binary_source = BinarySource()\n",
    "qam_source = QAMSource(num_bits_per_symbol)\n",
    "\n",
    "# The encoder maps information bits to coded bits\n",
    "encoder = LDPC5GEncoder(k, n)\n",
    "\n",
    "# The mapper maps blocks of information bits to constellation symbols\n",
    "mapper = Mapper(\"qam\", num_bits_per_symbol)\n",
    "\n",
    "# The resource grid mapper maps symbols onto an OFDM resource grid\n",
    "rg_mapper = ResourceGridMapper(rg)\n",
    "\n",
    "# This function removes nulled subcarriers from any tensor having the shape of a resource grid\n",
    "remove_nulled_scs = RemoveNulledSubcarriers(rg)\n",
    "\n",
    "# The LS channel estimator will provide channel estimates and error variances\n",
    "ls_est = LSChannelEstimator(rg, interpolation_type=\"nn\")\n",
    "\n",
    "# The LMMSE equalizer will provide soft symbols together with noise variance estimates\n",
    "lmmse_equ = LMMSEEqualizer(rg, sm)\n",
    "\n",
    "# The demapper produces LLR for all coded bits\n",
    "demapper = Demapper(\"app\", \"qam\", num_bits_per_symbol)\n",
    "\n",
    "# The decoder provides hard-decisions on the information bits\n",
    "decoder = LDPC5GDecoder(encoder, hard_out=True)\n",
    "\n",
    "# OFDM CHannel\n",
    "ofdm_channel = OFDMChannel(channel_model, rg, add_awgn=True, normalize_channel=False, return_channel=True)\n",
    "channel_freq = ApplyOFDMChannel(add_awgn=True)\n",
    "frequencies = subcarrier_frequencies(rg.fft_size, rg.subcarrier_spacing)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fb5aeee-618a-4ea8-95fe-536575ddc762",
   "metadata": {},
   "source": [
    "## Uplink Transmissions in the Frequency Domain\n",
    "\n",
    "We now simulate a batch of uplink transmissions. We keep references to the estimated and actual channel frequency responses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9ac4a821-136b-4e1a-9e2d-094c36c8a564",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:28.390254Z",
     "iopub.status.busy": "2025-03-11T00:48:28.389995Z",
     "iopub.status.idle": "2025-03-11T00:48:30.973688Z",
     "shell.execute_reply": "2025-03-11T00:48:30.972801Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BER: 0.0\n"
     ]
    }
   ],
   "source": [
    "ebno_db = 10\n",
    "no = ebnodb2no(ebno_db, num_bits_per_symbol, coderate, rg)\n",
    "b = binary_source([batch_size, num_ut, rg.num_streams_per_tx, encoder.k])\n",
    "c = encoder(b)\n",
    "x = mapper(c)\n",
    "x_rg = rg_mapper(x)\n",
    "\n",
    "a, tau = channel_model(num_time_samples=rg.num_ofdm_symbols, sampling_frequency=1/rg.ofdm_symbol_duration)\n",
    "h_freq = cir_to_ofdm_channel(frequencies, a, tau, normalize=True)\n",
    "\n",
    "y = channel_freq(x_rg, h_freq, no)\n",
    "h_hat, err_var = ls_est (y, no)\n",
    "x_hat, no_eff = lmmse_equ(y, h_hat, err_var, no)\n",
    "llr = demapper(x_hat, no_eff)\n",
    "b_hat = decoder(llr)\n",
    "print(\"BER: {}\".format(compute_ber(b, b_hat).numpy()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c7cca1c-8228-4668-a330-f0b853693cc2",
   "metadata": {},
   "source": [
    "### Compare Estimated and Actual Frequency Responses\n",
    "We can now compare the estimated frequency responses and ground truth:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d8a5a83e-f1ee-4e74-827f-f4b339ecc05b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:30.977457Z",
     "iopub.status.busy": "2025-03-11T00:48:30.977153Z",
     "iopub.status.idle": "2025-03-11T00:48:31.212342Z",
     "shell.execute_reply": "2025-03-11T00:48:31.211853Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# In the example above, we assumed perfect CSI, i.e.,\n",
    "# h_hat correpsond to the exact ideal channel frequency response.\n",
    "h_perf = remove_nulled_scs(h_freq)[0,0,0,0,0,0]\n",
    "\n",
    "# We now compute the LS channel estimate from the pilots.\n",
    "h_est = h_hat[0,0,0,0,0,0]\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(np.real(h_perf))\n",
    "plt.plot(np.imag(h_perf))\n",
    "plt.plot(np.real(h_est), \"--\")\n",
    "plt.plot(np.imag(h_est), \"--\")\n",
    "plt.xlabel(\"Subcarrier index\")\n",
    "plt.ylabel(\"Channel frequency response\")\n",
    "plt.legend([\"Ideal (real part)\", \"Ideal (imaginary part)\", \"Estimated (real part)\", \"Estimated (imaginary part)\"]);\n",
    "plt.title(\"Comparison of channel frequency responses\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45c3b321-b6b8-40ab-9620-1e8d609ad267",
   "metadata": {},
   "source": [
    "### Understand the Difference Between the Channel Models\n",
    "Before we proceed with more advanced simulations, it is important to understand the differences\n",
    "between the UMi, UMa, and RMa models. In the following code snippet, we compute the empirical cummulative\n",
    "distribution function (CDF) of the condition number of the channel frequency response matrix\n",
    "between all receiver and transmit antennas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9833e89e-64ae-4724-a191-7241fed6bac4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:31.215119Z",
     "iopub.status.busy": "2025-03-11T00:48:31.214801Z",
     "iopub.status.idle": "2025-03-11T00:48:35.643019Z",
     "shell.execute_reply": "2025-03-11T00:48:35.642399Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def cond_hist(scenario):\n",
    "    \"\"\"Generates a histogram of the channel condition numbers\"\"\"\n",
    "    \n",
    "    # Setup a CIR generator\n",
    "    if scenario == \"umi\":\n",
    "        channel_model = UMi(carrier_frequency=carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    elif scenario == \"uma\":\n",
    "        channel_model = UMa(carrier_frequency=carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    elif scenario == \"rma\":\n",
    "        channel_model = RMa(carrier_frequency=carrier_frequency,\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    \n",
    "    topology = gen_topology(1024, num_ut, scenario)\n",
    "\n",
    "    # Set the topology\n",
    "    channel_model.set_topology(*topology)\n",
    "    \n",
    "    # Generate random CIR realizations\n",
    "    # As we nned only a single sample in time, the sampling_frequency\n",
    "    # does not matter.\n",
    "    cir = channel_model(1, 1)\n",
    "    \n",
    "    # Compute the frequency response\n",
    "    h = cir_to_ofdm_channel(frequencies, *cir, normalize=True)\n",
    "    \n",
    "    h = tf.squeeze(h)\n",
    "    h = tf.transpose(h, [0,3,1,2])\n",
    "    \n",
    "    # Compute condition number\n",
    "    c = np.reshape(np.linalg.cond(h), [-1])\n",
    "    \n",
    "    # Compute normalized histogram\n",
    "    hist, bins = np.histogram(c, 100, (1, 100))\n",
    "    hist = hist/np.sum(hist)\n",
    "    return bins[:-1], hist\n",
    "\n",
    "plt.figure()\n",
    "for cdl_model in [\"umi\", \"uma\", \"rma\"]:\n",
    "    bins, hist = cond_hist(cdl_model)\n",
    "    plt.plot(bins, np.cumsum(hist))\n",
    "plt.xlim([0,40])\n",
    "plt.legend([\"UMi\", \"UMa\", \"RMa\"]);\n",
    "plt.xlabel(\"Channel Condition Number\")\n",
    "plt.ylabel(\"CDF\")\n",
    "plt.title(\"CDF of the channel condition number\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "535a6770-7857-4b28-9605-2f7699a5c6ad",
   "metadata": {},
   "source": [
    "From the figure above, you can observe that the UMi and UMa models\n",
    "are better conditioned than the RMa model. This makes \n",
    "them more suitable for MIMO transmissions as we will observe in the next\n",
    "section.\n",
    "\n",
    "It is also interesting to look at the channel frequency responses of these different models, as done in the next cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5d9d6c37-b96d-4967-804e-ec628209ba58",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:35.646333Z",
     "iopub.status.busy": "2025-03-11T00:48:35.646012Z",
     "iopub.status.idle": "2025-03-11T00:48:37.196701Z",
     "shell.execute_reply": "2025-03-11T00:48:37.196220Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def freq_response(scenario):\n",
    "    \"\"\"Generates an example frequency response\"\"\"\n",
    "    \n",
    "    # Setup a CIR generator\n",
    "    if scenario == \"umi\":\n",
    "        channel_model = UMi(carrier_frequency=carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    elif scenario == \"uma\":\n",
    "        channel_model = UMa(carrier_frequency=carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    elif scenario == \"rma\":\n",
    "        channel_model = RMa(carrier_frequency=carrier_frequency,\n",
    "                                      ut_array=ut_array,\n",
    "                                      bs_array=bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "    \n",
    "    topology = gen_topology(1, num_ut, scenario)\n",
    "\n",
    "    # Set the topology\n",
    "    channel_model.set_topology(*topology)\n",
    "    \n",
    "    # Generate random CIR realizations\n",
    "    # As we nned only a single sample in time, the sampling_frequency\n",
    "    # does not matter.\n",
    "    cir = channel_model(1, 1)\n",
    "    \n",
    "    # Compute the frequency response\n",
    "    h = cir_to_ofdm_channel(frequencies, *cir, normalize=True)\n",
    "    h = tf.squeeze(h)\n",
    "\n",
    "    return h[0,0]\n",
    "\n",
    "plt.figure()\n",
    "for cdl_model in [\"umi\", \"uma\", \"rma\"]:\n",
    "    h = freq_response(cdl_model)\n",
    "    plt.plot(np.real(h))\n",
    "plt.legend([\"UMi\", \"UMa\", \"RMa\"]);\n",
    "plt.xlabel(\"Subcarrier Index\")\n",
    "plt.ylabel(r\"$\\Re(h)$\")\n",
    "plt.title(\"Channel frequency response\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50b6b276-cc49-4c34-b230-da335fbe57c6",
   "metadata": {},
   "source": [
    "The RMa model has significantly less frequency selectivity than the other models which makes channel estimation easier."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c51efaff-c18c-4f26-87a4-e5a7b51b11ec",
   "metadata": {},
   "source": [
    "### Setup a Sionna Block for BER simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c9b30ed0-ad9e-4e47-8321-11a4a7c165a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:37.199741Z",
     "iopub.status.busy": "2025-03-11T00:48:37.199420Z",
     "iopub.status.idle": "2025-03-11T00:48:37.213644Z",
     "shell.execute_reply": "2025-03-11T00:48:37.213153Z"
    }
   },
   "outputs": [],
   "source": [
    "class Model(Block):\n",
    "    \"\"\"Simulate OFDM MIMO transmissions over a 3GPP 38.901 model\"\"\"\n",
    "    def __init__(self, scenario, perfect_csi):\n",
    "        super().__init__()\n",
    "        self._scenario = scenario\n",
    "        self._perfect_csi = perfect_csi\n",
    "        \n",
    "        # Internally set parameters\n",
    "        self._carrier_frequency = 3.5e9\n",
    "        self._fft_size = 128\n",
    "        self._subcarrier_spacing = 30e3\n",
    "        self._num_ofdm_symbols = 14\n",
    "        self._cyclic_prefix_length = 20\n",
    "        self._pilot_ofdm_symbol_indices = [2, 11]      \n",
    "        self._num_bs_ant = 8\n",
    "        self._num_ut = 4\n",
    "        self._num_ut_ant = 1\n",
    "        self._num_bits_per_symbol = 2 \n",
    "        self._coderate = 0.5\n",
    "    \n",
    "        # Create an RX-TX association matrix\n",
    "        # rx_tx_association[i,j]=1 means that receiver i gets at least one stream\n",
    "        # from transmitter j. Depending on the transmission direction (uplink or downlink),\n",
    "        # the role of UT and BS can change. \n",
    "        bs_ut_association = np.zeros([1, self._num_ut])\n",
    "        bs_ut_association[0, :] = 1\n",
    "        self._rx_tx_association = bs_ut_association\n",
    "        self._num_tx = self._num_ut\n",
    "        self._num_streams_per_tx = self._num_ut_ant\n",
    "\n",
    "        # Setup an OFDM Resource Grid\n",
    "        self._rg = ResourceGrid(num_ofdm_symbols=self._num_ofdm_symbols,\n",
    "                                fft_size=self._fft_size,\n",
    "                                subcarrier_spacing=self._subcarrier_spacing,\n",
    "                                num_tx=self._num_tx,\n",
    "                                num_streams_per_tx=self._num_streams_per_tx,\n",
    "                                cyclic_prefix_length=self._cyclic_prefix_length,\n",
    "                                pilot_pattern=\"kronecker\",\n",
    "                                pilot_ofdm_symbol_indices=self._pilot_ofdm_symbol_indices)\n",
    "\n",
    "        # Setup StreamManagement\n",
    "        self._sm = StreamManagement(self._rx_tx_association, self._num_streams_per_tx)\n",
    "\n",
    "        # Configure antenna arrays\n",
    "        self._ut_array = AntennaArray(\n",
    "                                 num_rows=1,\n",
    "                                 num_cols=1,\n",
    "                                 polarization=\"single\",\n",
    "                                 polarization_type=\"V\",\n",
    "                                 antenna_pattern=\"omni\",\n",
    "                                 carrier_frequency=self._carrier_frequency)\n",
    "\n",
    "        self._bs_array = AntennaArray(num_rows=1,\n",
    "                                      num_cols=int(self._num_bs_ant/2),\n",
    "                                      polarization=\"dual\",\n",
    "                                      polarization_type=\"cross\",\n",
    "                                      antenna_pattern=\"38.901\",\n",
    "                                      carrier_frequency=self._carrier_frequency)\n",
    "\n",
    "        # Configure the channel model\n",
    "        if self._scenario == \"umi\":\n",
    "            self._channel_model = UMi(carrier_frequency=self._carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=self._ut_array,\n",
    "                                      bs_array=self._bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "        elif self._scenario == \"uma\":\n",
    "            self._channel_model = UMa(carrier_frequency=self._carrier_frequency,\n",
    "                                      o2i_model=\"low\",\n",
    "                                      ut_array=self._ut_array,\n",
    "                                      bs_array=self._bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "        elif self._scenario == \"rma\":\n",
    "            self._channel_model = RMa(carrier_frequency=self._carrier_frequency,\n",
    "                                      ut_array=self._ut_array,\n",
    "                                      bs_array=self._bs_array,\n",
    "                                      direction=\"uplink\",\n",
    "                                      enable_pathloss=False,\n",
    "                                      enable_shadow_fading=False)\n",
    "\n",
    "        # Instantiate other building blocks\n",
    "        self._binary_source = BinarySource()\n",
    "        self._qam_source = QAMSource(self._num_bits_per_symbol)\n",
    "\n",
    "        self._n = int(self._rg.num_data_symbols*self._num_bits_per_symbol) # Number of coded bits\n",
    "        self._k = int(self._n*self._coderate)                              # Number of information bits\n",
    "        self._encoder = LDPC5GEncoder(self._k, self._n)\n",
    "        self._decoder = LDPC5GDecoder(self._encoder)\n",
    "        self._mapper = Mapper(\"qam\", self._num_bits_per_symbol)\n",
    "        self._rg_mapper = ResourceGridMapper(self._rg)\n",
    "\n",
    "        self._ofdm_channel = OFDMChannel(self._channel_model, self._rg, add_awgn=True,\n",
    "                                         normalize_channel=True, return_channel=True)\n",
    "\n",
    "        self._remove_nulled_subcarriers = RemoveNulledSubcarriers(self._rg)\n",
    "        self._ls_est = LSChannelEstimator(self._rg, interpolation_type=\"nn\")\n",
    "        self._lmmse_equ = LMMSEEqualizer(self._rg, self._sm)\n",
    "        self._demapper = Demapper(\"app\", \"qam\", self._num_bits_per_symbol)\n",
    "\n",
    "    def new_topology(self, batch_size):\n",
    "        \"\"\"Set new topology\"\"\"\n",
    "        topology = gen_topology(batch_size,\n",
    "                                self._num_ut,\n",
    "                                self._scenario,\n",
    "                                min_ut_velocity=0.0,\n",
    "                                max_ut_velocity=0.0)\n",
    "\n",
    "        self._channel_model.set_topology(*topology)\n",
    "\n",
    "    @tf.function # Run in graph mode. See the following guide: https://www.tensorflow.org/guide/function\n",
    "    def call(self, batch_size, ebno_db):        \n",
    "        self.new_topology(batch_size) \n",
    "        no = ebnodb2no(ebno_db, self._num_bits_per_symbol, self._coderate, self._rg)\n",
    "        b = self._binary_source([batch_size, self._num_tx, self._num_streams_per_tx, self._k])\n",
    "        c = self._encoder(b)\n",
    "        x = self._mapper(c)\n",
    "        x_rg = self._rg_mapper(x)   \n",
    "        y, h = self._ofdm_channel(x_rg, no)\n",
    "        if self._perfect_csi:\n",
    "            h_hat = self._remove_nulled_subcarriers(h)\n",
    "            err_var = 0.0\n",
    "        else:\n",
    "            h_hat, err_var = self._ls_est (y, no)\n",
    "        x_hat, no_eff = self._lmmse_equ(y, h_hat, err_var, no)\n",
    "        llr = self._demapper(x_hat, no_eff)\n",
    "        b_hat = self._decoder(llr)\n",
    "        return b, b_hat "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fc8be0d-96fb-4c15-9234-0c13efa1250a",
   "metadata": {},
   "source": [
    "If you do not want to run the simulations (which can take quite some time) yourself, you can skip the next cell and simply look at the results in the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fbe0e7ab-69fb-4f23-9dd9-23773a6c6655",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T00:48:37.216815Z",
     "iopub.status.busy": "2025-03-11T00:48:37.216498Z",
     "iopub.status.idle": "2025-03-11T01:42:15.845301Z",
     "shell.execute_reply": "2025-03-11T01:42:15.844236Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 2.9853e-02 | 3.1083e-01 |      164339 |     5505024 |         1114 |        3584 |        16.0 |reached target block errors\n",
      "     -3.0 | 2.1289e-03 | 2.3344e-02 |      140635 |    66060288 |         1004 |       43008 |        15.3 |reached target block errors\n",
      "     -1.0 | 2.3283e-04 | 2.4692e-03 |      144837 |   622067712 |         1000 |      404992 |       144.2 |reached target block errors\n",
      "      1.0 | 4.4132e-05 | 4.1602e-04 |       34707 |   786432000 |          213 |      512000 |       182.2 |reached max iterations\n",
      "\n",
      "Simulation stopped as target BLER is reached @ EbNo = 1.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 2.8675e-01 | 1.0000e+00 |      451019 |     1572864 |         1024 |        1024 |         6.3 |reached target block errors\n",
      "     -3.0 | 2.0428e-01 | 9.9219e-01 |      321301 |     1572864 |         1016 |        1024 |         0.4 |reached target block errors\n",
      "     -1.0 | 5.7570e-02 | 4.2266e-01 |      226375 |     3932160 |         1082 |        2560 |         0.9 |reached target block errors\n",
      "      1.0 | 9.1701e-03 | 6.8898e-02 |      209138 |    22806528 |         1023 |       14848 |         5.3 |reached target block errors\n",
      "      3.0 | 2.0201e-03 | 1.2868e-02 |      243071 |   120324096 |         1008 |       78336 |        28.2 |reached target block errors\n",
      "      5.0 | 6.8211e-04 | 3.6995e-03 |      283775 |   416022528 |         1002 |      270848 |        97.4 |reached target block errors\n",
      "      7.0 | 4.0859e-04 | 1.9570e-03 |      321327 |   786432000 |         1002 |      512000 |       184.2 |reached target block errors\n",
      "      9.0 | 3.3603e-04 | 1.6172e-03 |      264263 |   786432000 |          828 |      512000 |       184.2 |reached max iterations\n",
      "     11.0 | 3.1456e-04 | 1.7227e-03 |      247378 |   786432000 |          882 |      512000 |       184.0 |reached max iterations\n",
      "     13.0 | 3.3100e-04 | 1.9910e-03 |      255361 |   771489792 |         1000 |      502272 |       180.7 |reached target block errors\n",
      "     15.0 | 3.4906e-04 | 2.2870e-03 |      234434 |   671612928 |         1000 |      437248 |       157.4 |reached target block errors\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 3.0276e-02 | 3.2087e-01 |      166668 |     5505024 |         1150 |        3584 |         7.4 |reached target block errors\n",
      "     -3.0 | 2.1587e-03 | 2.3743e-02 |      140904 |    65273856 |         1009 |       42496 |        15.4 |reached target block errors\n",
      "     -1.0 | 1.5645e-04 | 1.8203e-03 |      123036 |   786432000 |          932 |      512000 |       185.6 |reached max iterations\n",
      "      1.0 | 1.6736e-05 | 1.8359e-04 |       13162 |   786432000 |           94 |      512000 |       185.6 |reached max iterations\n",
      "\n",
      "Simulation stopped as target BLER is reached @ EbNo = 1.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 2.8923e-01 | 1.0000e+00 |      454913 |     1572864 |         1024 |        1024 |         6.3 |reached target block errors\n",
      "     -3.0 | 2.1206e-01 | 9.9609e-01 |      333540 |     1572864 |         1020 |        1024 |         0.4 |reached target block errors\n",
      "     -1.0 | 6.6101e-02 | 4.5859e-01 |      259921 |     3932160 |         1174 |        2560 |         0.9 |reached target block errors\n",
      "      1.0 | 1.0773e-02 | 7.7449e-02 |      220282 |    20447232 |         1031 |       13312 |         4.8 |reached target block errors\n",
      "      3.0 | 2.3180e-03 | 1.3782e-02 |      258862 |   111673344 |         1002 |       72704 |        26.2 |reached target block errors\n",
      "      5.0 | 1.2547e-03 | 5.8477e-03 |      331548 |   264241152 |         1006 |      172032 |        62.0 |reached target block errors\n",
      "      7.0 | 8.9402e-04 | 3.8946e-03 |      352951 |   394788864 |         1001 |      257024 |        92.6 |reached target block errors\n",
      "      9.0 | 7.9058e-04 | 3.6169e-03 |      335739 |   424673280 |         1000 |      276480 |        99.4 |reached target block errors\n",
      "     11.0 | 7.2924e-04 | 3.8260e-03 |      293059 |   401866752 |         1001 |      261632 |        94.4 |reached target block errors\n",
      "     13.0 | 7.4026e-04 | 4.2087e-03 |      270708 |   365690880 |         1002 |      238080 |        85.6 |reached target block errors\n",
      "     15.0 | 8.0186e-04 | 4.8562e-03 |      254134 |   316932096 |         1002 |      206336 |        74.4 |reached target block errors\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 4.2893e-02 | 3.3203e-01 |      202394 |     4718592 |         1020 |        3072 |         6.5 |reached target block errors\n",
      "     -3.0 | 8.5562e-03 | 7.3857e-02 |      181680 |    21233664 |         1021 |       13824 |         4.6 |reached target block errors\n",
      "     -1.0 | 2.2393e-03 | 1.9609e-02 |      177865 |    79429632 |         1014 |       51712 |        17.4 |reached target block errors\n",
      "      1.0 | 5.5664e-04 | 4.9847e-03 |      172040 |   309067776 |         1003 |      201216 |        67.6 |reached target block errors\n",
      "      3.0 | 1.5654e-04 | 1.4062e-03 |      123107 |   786432000 |          720 |      512000 |       171.9 |reached max iterations\n",
      "      5.0 | 3.9716e-05 | 4.0820e-04 |       31234 |   786432000 |          209 |      512000 |       172.0 |reached max iterations\n",
      "\n",
      "Simulation stopped as target BLER is reached @ EbNo = 5.0 dB.\n",
      "\n",
      "EbNo [dB] |        BER |       BLER |  bit errors |    num bits | block errors |  num blocks | runtime [s] |    status\n",
      "---------------------------------------------------------------------------------------------------------------------------------------\n",
      "     -5.0 | 2.8225e-01 | 1.0000e+00 |      443941 |     1572864 |         1024 |        1024 |         5.9 |reached target block errors\n",
      "     -3.0 | 1.8805e-01 | 9.6745e-01 |      443676 |     2359296 |         1486 |        1536 |         0.5 |reached target block errors\n",
      "     -1.0 | 6.5478e-02 | 3.6849e-01 |      308964 |     4718592 |         1132 |        3072 |         1.0 |reached target block errors\n",
      "      1.0 | 2.0988e-02 | 1.2415e-01 |      264091 |    12582912 |         1017 |        8192 |         2.8 |reached target block errors\n",
      "      3.0 | 7.2721e-03 | 4.3436e-02 |      263076 |    36175872 |         1023 |       23552 |         7.9 |reached target block errors\n",
      "      5.0 | 2.4428e-03 | 1.4634e-02 |      257426 |   105381888 |         1004 |       68608 |        23.1 |reached target block errors\n",
      "      7.0 | 9.1098e-04 | 5.4265e-03 |      258629 |   283901952 |         1003 |      184832 |        62.1 |reached target block errors\n",
      "      9.0 | 2.9875e-04 | 1.7813e-03 |      234950 |   786432000 |          912 |      512000 |       172.1 |reached max iterations\n",
      "     11.0 | 1.1107e-04 | 6.7383e-04 |       87351 |   786432000 |          345 |      512000 |       172.0 |reached max iterations\n",
      "\n",
      "Simulation stopped as target BLER is reached @ EbNo = 11.0 dB.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "SIMS = {\n",
    "    \"ebno_db\" : list(np.arange(-5, 17, 2.0)),\n",
    "    \"scenario\" : [\"umi\", \"uma\", \"rma\"],\n",
    "    \"perfect_csi\" : [True, False],\n",
    "    \"ber\" : [],\n",
    "    \"bler\" : [],\n",
    "    \"duration\" : None\n",
    "}\n",
    "\n",
    "start = time.time()\n",
    "\n",
    "for scenario in SIMS[\"scenario\"]:\n",
    "    for perfect_csi in SIMS[\"perfect_csi\"]:\n",
    "\n",
    "        model = Model(scenario=scenario,\n",
    "                      perfect_csi=perfect_csi)\n",
    "\n",
    "        ber, bler = sim_ber(model,\n",
    "                            SIMS[\"ebno_db\"],\n",
    "                            batch_size=128,\n",
    "                            max_mc_iter=1000,\n",
    "                            num_target_block_errors=1000,\n",
    "                            target_bler=1e-3)\n",
    "\n",
    "        SIMS[\"ber\"].append(list(ber.numpy()))\n",
    "        SIMS[\"bler\"].append(list(bler.numpy()))\n",
    "\n",
    "SIMS[\"duration\"] = time.time() -  start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7c0427ed-c7fd-4593-9cdb-13d8876b261f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-03-11T01:42:15.848233Z",
     "iopub.status.busy": "2025-03-11T01:42:15.847982Z",
     "iopub.status.idle": "2025-03-11T01:42:16.346406Z",
     "shell.execute_reply": "2025-03-11T01:42:16.345633Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.xlabel(r\"$E_b/N_0$ (dB)\")\n",
    "plt.ylabel(\"BLER\")\n",
    "plt.grid(which=\"both\")\n",
    "\n",
    "i=0\n",
    "legend = []\n",
    "for scenario in SIMS[\"scenario\"]:\n",
    "    for perfect_csi in SIMS[\"perfect_csi\"]:\n",
    "        if scenario==\"umi\":\n",
    "            r = \"r\"\n",
    "            t = \"UMi\"\n",
    "        elif scenario==\"uma\":\n",
    "            r = \"b\"\n",
    "            t = \"UMa\"\n",
    "        else:\n",
    "            r = \"g\"\n",
    "            t = \"RMa\"\n",
    "        if perfect_csi:\n",
    "            r += \"-\"\n",
    "        else:\n",
    "            r += \"--\"\n",
    "\n",
    "        plt.semilogy(SIMS[\"ebno_db\"], SIMS[\"bler\"][i], r);\n",
    "        s = \"{} - {} CSI\".format(t,\"perf.\" if perfect_csi else \"imperf.\")\n",
    "\n",
    "        legend.append(s)\n",
    "        i += 1\n",
    "plt.legend(legend)\n",
    "plt.ylim([1e-4, 1])\n",
    "plt.title(\"Multiuser 4x8 MIMO Uplink over Different 3GPP 38.901 Models\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53a18c80-2bba-449a-b2c2-5e75ee2196f6",
   "metadata": {},
   "source": [
    "Due to the worse channel conditioning, the RMa model achieves the worst performance with perfect CSI. However, as a result of the smaller frequency selectivity, imperfect channel estimation only leads to an almost constant 6dB performace loss. For the UMI and UMa models, the used channel estimator with nearest-neighbor interpolation is not accurate enough so that the BER curves saturate at high SNR. This could, for example, be circumvented with another interpolation method (e.g., [linear interpolation with time averaging](https://nvlabs.github.io/sionna/phy/phy/api/ofdm.html#sionna.phy.ofdm.LinearInterpolator)) or a different pilot pattern."
   ]
  }
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